@@ -178,7 +178,16 @@ def tabulate_result_tests(
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algorithm ID and returns an instance name; default=identity function
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:param use_lang: should we use the language to define the filename
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:param p_renderer: the renderer for all probabilities
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- :param value_getter: the getter for the values that should be compared
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+ :param value_getter: the getter for the values that should be compared. By
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+ default, the best obtained objective values are compared. However, if
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+ you let the runs continue until they reach a certain goal quality,
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+ then you may want to compare the runtimes consumed until that quality
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+ is reached. Basically, you can use any of the getters provided by
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+ :meth:`moptipy.evaluation.end_results.EndResult.getter`, but you must
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+ take care that the comparison makes sense, i.e., compare qualities
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+ under fixed-budget scenarios (the default behavior) or compare
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+ runtimes under scenarios with goal qualities - but do not mix up the
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+ scenarios.
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:returns: the path to the file with the tabulated test results
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"""
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# Before doing anything, let's do some type checking on the parameters.
@@ -319,7 +328,7 @@ def tabulate_result_tests(
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alpha_prime )
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for j in range (n_insts )]
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for i in range (n_cols )]
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- cols .insert (0 , [FormattedStr (instance_namer (inst ), code = True )
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+ cols .insert (0 , [FormattedStr . add_format (instance_namer (inst ), code = True )
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for inst in instances ])
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# We now got the p_values, the comparison results, and the p_strs.
@@ -358,8 +367,10 @@ def __app(a, b):
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"'=" , alpha_prime_str ])
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for i in range (n_algos - 1 ):
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for j in range (i + 1 , n_algos ):
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- an1 = FormattedStr (algorithm_namer (algorithms [i ]), code = True )
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- an2 = FormattedStr (algorithm_namer (algorithms [j ]), code = True )
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+ an1 = FormattedStr .add_format (algorithm_namer (algorithms [i ]),
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+ code = True )
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+ an2 = FormattedStr .add_format (algorithm_namer (algorithms [j ]),
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+ code = True )
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if len (an1 ) >= len (an2 ):
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__app (an1 , ["vs. " , an2 ])
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else :
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